An Adaptive Web Page Recommendation Service

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An Adaptive Web Page Recommendation Service
An adaptive recommendation service seeks to adapt to its users, providing increasingly personalized recommendations over time. In this paper we introduce the \Fab" adaptive Web page recommendation service. There has been much research on analyzing document content in order to improve recommendations or search results. More recently researchers have begun to explore how the similarities between users can be exploited to the same ends. The Fab system strikes a balance between these two approaches, taking advantage of the shared interests among users without losing the bene ts of the representations provided by content analysis. Running since March 1996, it has been populated with a collection of agents for the collection and selection of Web pages, whose interaction fosters emergent collaborative properties. In this paper we explain the design of the system architecture and report the results of our rst experiment, evaluating recommendations provided to a group of test users.
Marko Balabanovic
Added 07 Aug 2010
Updated 07 Aug 2010
Type Conference
Year 1997
Authors Marko Balabanovic
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